Overview

Dataset statistics

Number of variables29
Number of observations4059009
Missing cells5692679
Missing cells (%)4.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory929.0 MiB
Average record size in memory240.0 B

Variable types

Numeric4
Categorical22
DateTime2
Unsupported1

Alerts

ZavA has constant value ""Constant
ZavB has constant value ""Constant
ZavC has constant value ""Constant
Zav0 has constant value ""Constant
Zav1 has constant value ""Constant
Zav2 has constant value ""Constant
Zav3 has constant value ""Constant
Zav4 has constant value ""Constant
Zav5 has constant value ""Constant
Zav6 has constant value ""Constant
Zav7 has constant value ""Constant
Zav8 has constant value ""Constant
Zav9 has constant value ""Constant
VIN has a high cardinality: 3364348 distinct valuesHigh cardinality
TypMot has a high cardinality: 65776 distinct valuesHigh cardinality
TZn has a high cardinality: 6587 distinct valuesHigh cardinality
ObchOznTyp has a high cardinality: 70031 distinct valuesHigh cardinality
Ct has a high cardinality: 134 distinct valuesHigh cardinality
DrTP is highly imbalanced (62.8%)Imbalance
TZn is highly imbalanced (59.0%)Imbalance
DrVoz is highly imbalanced (71.0%)Imbalance
Ct is highly imbalanced (72.6%)Imbalance
VyslSTK is highly imbalanced (74.4%)Imbalance
VyslEmise is highly imbalanced (98.0%)Imbalance
TypMot has 191070 (4.7%) missing valuesMissing
Zavady has 4059009 (100.0%) missing valuesMissing
VyslEmise has 1440714 (35.5%) missing valuesMissing
VIN is uniformly distributedUniform
Zavady is an unsupported type, check if it needs cleaning or further analysisUnsupported
Km has 312244 (7.7%) zerosZeros

Reproduction

Analysis started2023-03-30 19:16:45.438164
Analysis finished2023-03-30 19:21:29.143231
Duration4 minutes and 43.71 seconds
Software versionydata-profiling vv4.1.2
Download configurationconfig.json

Variables

STK
Real number (ℝ)

Distinct554
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3525.8334
Minimum3100
Maximum9999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.9 MiB
2023-03-30T21:21:29.212563image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum3100
5-th percentile3114
Q13245
median3524
Q33739
95-th percentile3842
Maximum9999
Range6899
Interquartile range (IQR)494

Descriptive statistics

Standard deviation340.02741
Coefficient of variation (CV)0.096438874
Kurtosis58.913147
Mean3525.8334
Median Absolute Deviation (MAD)220
Skewness5.1315009
Sum1.431139 × 1010
Variance115618.64
MonotonicityNot monotonic
2023-03-30T21:21:29.315367image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3413 80057
 
2.0%
3307 55193
 
1.4%
3851 38397
 
0.9%
3112 36335
 
0.9%
3766 34343
 
0.8%
3114 34111
 
0.8%
3243 30227
 
0.7%
3523 29923
 
0.7%
3609 29906
 
0.7%
3754 29122
 
0.7%
Other values (544) 3661395
90.2%
ValueCountFrequency (%)
3100 20435
0.5%
3102 14263
0.4%
3103 2830
 
0.1%
3104 21605
0.5%
3105 17626
0.4%
3106 25364
0.6%
3107 4128
 
0.1%
3108 17825
0.4%
3109 6719
 
0.2%
3110 12631
0.3%
ValueCountFrequency (%)
9999 29
< 0.1%
9998 1
 
< 0.1%
9911 3
 
< 0.1%
8901 6
 
< 0.1%
8871 37
< 0.1%
8870 46
< 0.1%
8866 4
 
< 0.1%
8865 5
 
< 0.1%
8861 5
 
< 0.1%
8860 5
 
< 0.1%

DrTP
Categorical

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
pravidelná
2691738 
Evidenční kontrola
893095 
opakovaná
 
229921
Před registrací
 
202870
Na žádost zákazníka
 
19745
Other values (9)
 
21640

Length

Max length46
Median length10
Mean length12.062621
Min length3

Characters and Unicode

Total characters48962289
Distinct characters37
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEvidenční kontrola
2nd rowEvidenční kontrola
3rd rowEvidenční kontrola
4th rowEvidenční kontrola
5th rowEvidenční kontrola

Common Values

ValueCountFrequency (%)
pravidelná 2691738
66.3%
Evidenční kontrola 893095
 
22.0%
opakovaná 229921
 
5.7%
Před registrací 202870
 
5.0%
Na žádost zákazníka 19745
 
0.5%
Před schvál. tech. způsob. vozidla 5785
 
0.1%
ADR 4713
 
0.1%
Před registrací - opakovaná 4235
 
0.1%
Technická silniční kontrola 2948
 
0.1%
TSK - Opakovaná 1833
 
< 0.1%
Other values (4) 2126
 
0.1%

Length

2023-03-30T21:21:29.415476image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pravidelná 2691738
51.3%
kontrola 896043
 
17.1%
evidenční 893095
 
17.0%
opakovaná 237952
 
4.5%
před 213117
 
4.1%
registrací 207105
 
3.9%
na 19745
 
0.4%
žádost 19745
 
0.4%
zákazníka 19745
 
0.4%
8031
 
0.2%
Other values (12) 41513
 
0.8%

Most occurring characters

ValueCountFrequency (%)
n 5640838
11.5%
a 4336363
8.9%
e 4014341
8.2%
r 4002154
8.2%
v 3834809
 
7.8%
d 3823870
 
7.8%
i 3806957
 
7.8%
l 3602916
 
7.4%
á 2978466
 
6.1%
p 2937264
 
6.0%
Other values (27) 9984311
20.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 46587458
95.1%
Space Separator 1188820
 
2.4%
Uppercase Letter 1159944
 
2.4%
Other Punctuation 18036
 
< 0.1%
Dash Punctuation 8031
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 5640838
12.1%
a 4336363
9.3%
e 4014341
8.6%
r 4002154
8.6%
v 3834809
8.2%
d 3823870
8.2%
i 3806957
8.2%
l 3602916
7.7%
á 2978466
 
6.4%
p 2937264
 
6.3%
Other values (14) 7609480
16.3%
Uppercase Letter
ValueCountFrequency (%)
E 893095
77.0%
P 213117
 
18.4%
N 21307
 
1.8%
D 6449
 
0.6%
T 6180
 
0.5%
R 5050
 
0.4%
A 5050
 
0.4%
S 3232
 
0.3%
K 3232
 
0.3%
O 3232
 
0.3%
Space Separator
ValueCountFrequency (%)
1188820
100.0%
Other Punctuation
ValueCountFrequency (%)
. 18036
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8031
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 47747402
97.5%
Common 1214887
 
2.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 5640838
11.8%
a 4336363
9.1%
e 4014341
8.4%
r 4002154
8.4%
v 3834809
8.0%
d 3823870
8.0%
i 3806957
8.0%
l 3602916
7.5%
á 2978466
 
6.2%
p 2937264
 
6.2%
Other values (24) 8769424
18.4%
Common
ValueCountFrequency (%)
1188820
97.9%
. 18036
 
1.5%
- 8031
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43725524
89.3%
None 5236765
 
10.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 5640838
12.9%
a 4336363
9.9%
e 4014341
9.2%
r 4002154
9.2%
v 3834809
8.8%
d 3823870
8.7%
i 3806957
8.7%
l 3602916
8.2%
p 2937264
6.7%
o 2298089
5.3%
Other values (21) 5427923
12.4%
None
ValueCountFrequency (%)
á 2978466
56.9%
í 1123219
 
21.4%
č 896043
 
17.1%
ř 213280
 
4.1%
ž 19745
 
0.4%
ů 6012
 
0.1%

VIN
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct3364348
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
-
 
37
005
 
32
001
 
31
003
 
28
008
 
27
Other values (3364343)
4058854 

Length

Max length22
Median length17
Mean length16.467171
Min length1

Characters and Unicode

Total characters66840395
Distinct characters49
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2784745 ?
Unique (%)68.6%

Sample

1st rowJMZBLA2G601258504
2nd row4150417
3rd rowVF3MJAHXHGS280168
4th row4699845
5th rowWF0SXXGCDSAU06730

Common Values

ValueCountFrequency (%)
- 37
 
< 0.1%
005 32
 
< 0.1%
001 31
 
< 0.1%
003 28
 
< 0.1%
008 27
 
< 0.1%
004 25
 
< 0.1%
106 25
 
< 0.1%
033 24
 
< 0.1%
TEST0000000000001 23
 
< 0.1%
105 22
 
< 0.1%
Other values (3364338) 4058735
> 99.9%

Length

2023-03-30T21:21:29.647285image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
39
 
< 0.1%
005 32
 
< 0.1%
001 31
 
< 0.1%
003 28
 
< 0.1%
008 27
 
< 0.1%
004 25
 
< 0.1%
106 25
 
< 0.1%
033 24
 
< 0.1%
test0000000000001 23
 
< 0.1%
105 22
 
< 0.1%
Other values (3364265) 4058780
> 99.9%

Most occurring characters

ValueCountFrequency (%)
0 6969357
 
10.4%
1 5423292
 
8.1%
2 4252861
 
6.4%
3 3928084
 
5.9%
5 3500165
 
5.2%
6 3453013
 
5.2%
4 3450533
 
5.2%
7 3082049
 
4.6%
8 2926508
 
4.4%
Z 2692397
 
4.0%
Other values (39) 27162136
40.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39618132
59.3%
Uppercase Letter 27137856
40.6%
Dash Punctuation 47537
 
0.1%
Other Punctuation 36814
 
0.1%
Space Separator 48
 
< 0.1%
Math Symbol 5
 
< 0.1%
Connector Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Z 2692397
 
9.9%
B 2183189
 
8.0%
F 1950034
 
7.2%
W 1881823
 
6.9%
A 1720316
 
6.3%
M 1688821
 
6.2%
T 1664613
 
6.1%
V 1379818
 
5.1%
J 1097871
 
4.0%
X 1086217
 
4.0%
Other values (17) 9792757
36.1%
Decimal Number
ValueCountFrequency (%)
0 6969357
17.6%
1 5423292
13.7%
2 4252861
10.7%
3 3928084
9.9%
5 3500165
8.8%
6 3453013
8.7%
4 3450533
8.7%
7 3082049
7.8%
8 2926508
7.4%
9 2632270
 
6.6%
Other Punctuation
ValueCountFrequency (%)
/ 35515
96.5%
. 857
 
2.3%
% 360
 
1.0%
* 73
 
0.2%
, 7
 
< 0.1%
" 2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 47537
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Math Symbol
ValueCountFrequency (%)
+ 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39702539
59.4%
Latin 27137856
40.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
Z 2692397
 
9.9%
B 2183189
 
8.0%
F 1950034
 
7.2%
W 1881823
 
6.9%
A 1720316
 
6.3%
M 1688821
 
6.2%
T 1664613
 
6.1%
V 1379818
 
5.1%
J 1097871
 
4.0%
X 1086217
 
4.0%
Other values (17) 9792757
36.1%
Common
ValueCountFrequency (%)
0 6969357
17.6%
1 5423292
13.7%
2 4252861
10.7%
3 3928084
9.9%
5 3500165
8.8%
6 3453013
8.7%
4 3450533
8.7%
7 3082049
7.8%
8 2926508
7.4%
9 2632270
 
6.6%
Other values (12) 84407
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66840394
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6969357
 
10.4%
1 5423292
 
8.1%
2 4252861
 
6.4%
3 3928084
 
5.9%
5 3500165
 
5.2%
6 3453013
 
5.2%
4 3450533
 
5.2%
7 3082049
 
4.6%
8 2926508
 
4.4%
Z 2692397
 
4.0%
Other values (38) 27162135
40.6%
None
ValueCountFrequency (%)
Š 1
100.0%
Distinct4047748
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
Minimum2018-01-01 19:16:51.897000
Maximum2018-12-31 16:07:02.557000
2023-03-30T21:21:29.761686image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:21:29.848184image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

TypMot
Categorical

HIGH CARDINALITY  MISSING 

Distinct65776
Distinct (%)1.7%
Missing191070
Missing (%)4.7%
Memory size61.9 MiB
-
 
99450
BXE
 
39463
ALH
 
36402
781.136M
 
34286
CBZA
 
27716
Other values (65771)
3630622 

Length

Max length17
Median length16
Mean length4.6005136
Min length1

Characters and Unicode

Total characters17794506
Distinct characters104
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33487 ?
Unique (%)0.9%

Sample

1st rowLF
2nd rowEM150.2
3rd rowAH01
4th row1202
5th rowGPDC

Common Values

ValueCountFrequency (%)
- 99450
 
2.5%
BXE 39463
 
1.0%
ALH 36402
 
0.9%
781.136M 34286
 
0.8%
CBZA 27716
 
0.7%
AQW 27428
 
0.7%
G4FA 25584
 
0.6%
ASV 25307
 
0.6%
AGR 25171
 
0.6%
AZQ 24514
 
0.6%
Other values (65766) 3502618
86.3%
(Missing) 191070
 
4.7%

Length

2023-03-30T21:21:29.948125image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
107169
 
2.4%
bxe 39466
 
0.9%
alh 36465
 
0.8%
m 36003
 
0.8%
7 35549
 
0.8%
781.136m 34704
 
0.8%
781.136 34511
 
0.8%
cbza 27718
 
0.6%
aqw 27677
 
0.6%
d 27455
 
0.6%
Other values (49581) 3971756
90.7%

Most occurring characters

ValueCountFrequency (%)
A 1380521
 
7.8%
1 1153237
 
6.5%
B 922863
 
5.2%
F 864960
 
4.9%
0 850419
 
4.8%
4 830479
 
4.7%
D 735660
 
4.1%
C 721569
 
4.1%
2 621409
 
3.5%
6 590955
 
3.3%
Other values (94) 9122434
51.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 10339186
58.1%
Decimal Number 6353450
35.7%
Space Separator 512546
 
2.9%
Other Punctuation 364102
 
2.0%
Dash Punctuation 220135
 
1.2%
Math Symbol 2652
 
< 0.1%
Open Punctuation 1039
 
< 0.1%
Close Punctuation 1013
 
< 0.1%
Lowercase Letter 372
 
< 0.1%
Connector Punctuation 6
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1380521
13.4%
B 922863
 
8.9%
F 864960
 
8.4%
D 735660
 
7.1%
C 721569
 
7.0%
E 559023
 
5.4%
M 493307
 
4.8%
H 476627
 
4.6%
Z 383728
 
3.7%
K 378792
 
3.7%
Other values (29) 3422136
33.1%
Lowercase Letter
ValueCountFrequency (%)
a 36
 
9.7%
f 35
 
9.4%
š 32
 
8.6%
b 30
 
8.1%
c 23
 
6.2%
d 22
 
5.9%
z 19
 
5.1%
s 18
 
4.8%
ý 18
 
4.8%
h 14
 
3.8%
Other values (21) 125
33.6%
Other Punctuation
ValueCountFrequency (%)
. 305248
83.8%
/ 41220
 
11.3%
, 10965
 
3.0%
* 6520
 
1.8%
? 101
 
< 0.1%
: 21
 
< 0.1%
; 19
 
< 0.1%
" 3
 
< 0.1%
& 2
 
< 0.1%
! 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 1153237
18.2%
0 850419
13.4%
4 830479
13.1%
2 621409
9.8%
6 590955
9.3%
7 526301
8.3%
3 525872
8.3%
8 489312
7.7%
9 403846
 
6.4%
5 361620
 
5.7%
Modifier Symbol
ValueCountFrequency (%)
¨ 3
60.0%
˙ 1
 
20.0%
´ 1
 
20.0%
Math Symbol
ValueCountFrequency (%)
+ 2651
> 99.9%
| 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 1038
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1012
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
512546
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 220135
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10339558
58.1%
Common 7454948
41.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1380521
13.4%
B 922863
 
8.9%
F 864960
 
8.4%
D 735660
 
7.1%
C 721569
 
7.0%
E 559023
 
5.4%
M 493307
 
4.8%
H 476627
 
4.6%
Z 383728
 
3.7%
K 378792
 
3.7%
Other values (60) 3422508
33.1%
Common
ValueCountFrequency (%)
1 1153237
15.5%
0 850419
11.4%
4 830479
11.1%
2 621409
8.3%
6 590955
7.9%
7 526301
7.1%
3 525872
7.1%
512546
6.9%
8 489312
6.6%
9 403846
 
5.4%
Other values (24) 950572
12.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17787595
> 99.9%
None 6910
 
< 0.1%
Modifier Letters 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 1380521
 
7.8%
1 1153237
 
6.5%
B 922863
 
5.2%
F 864960
 
4.9%
0 850419
 
4.8%
4 830479
 
4.7%
D 735660
 
4.1%
C 721569
 
4.1%
2 621409
 
3.5%
6 590955
 
3.3%
Other values (73) 9115523
51.2%
None
ValueCountFrequency (%)
Š 4883
70.7%
Č 1378
 
19.9%
Á 238
 
3.4%
Ý 122
 
1.8%
Í 82
 
1.2%
Ř 55
 
0.8%
Ž 37
 
0.5%
Ě 32
 
0.5%
š 32
 
0.5%
ý 18
 
0.3%
Other values (10) 33
 
0.5%
Modifier Letters
ValueCountFrequency (%)
˙ 1
100.0%

TZn
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct6587
Distinct (%)0.2%
Missing902
Missing (%)< 0.1%
Memory size61.9 MiB
ŠKODA
978586 
FORD
282660 
RENAULT
 
209506
PEUGEOT
 
196811
VOLKSWAGEN
 
181840
Other values (6582)
2208704 

Length

Max length30
Median length29
Mean length5.7732849
Min length1

Characters and Unicode

Total characters23428608
Distinct characters112
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2954 ?
Unique (%)0.1%

Sample

1st rowMAZDA
2nd rowMZ
3rd rowPEUGEOT
4th rowŠKODA
5th rowFORD

Common Values

ValueCountFrequency (%)
ŠKODA 978586
24.1%
FORD 282660
 
7.0%
RENAULT 209506
 
5.2%
PEUGEOT 196811
 
4.8%
VOLKSWAGEN 181840
 
4.5%
VW 178805
 
4.4%
CITROËN 141376
 
3.5%
OPEL 124020
 
3.1%
MERCEDES-BENZ 114571
 
2.8%
HYUNDAI 103290
 
2.5%
Other values (6577) 1546642
38.1%

Length

2023-03-30T21:21:30.054770image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
škoda 978609
23.4%
ford 282669
 
6.8%
renault 209577
 
5.0%
peugeot 196813
 
4.7%
volkswagen 181840
 
4.3%
vw 178808
 
4.3%
citroën 141376
 
3.4%
opel 124021
 
3.0%
mercedes-benz 114573
 
2.7%
hyundai 103290
 
2.5%
Other values (6172) 1670181
39.9%

Most occurring characters

ValueCountFrequency (%)
A 2875124
 
12.3%
O 2601571
 
11.1%
D 1826762
 
7.8%
E 1741915
 
7.4%
K 1368253
 
5.8%
N 1119683
 
4.8%
R 1115847
 
4.8%
T 1104328
 
4.7%
Š 981818
 
4.2%
I 914970
 
3.9%
Other values (102) 7778337
33.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 23137117
98.8%
Space Separator 140282
 
0.6%
Dash Punctuation 126043
 
0.5%
Lowercase Letter 11115
 
< 0.1%
Decimal Number 7640
 
< 0.1%
Other Punctuation 6195
 
< 0.1%
Math Symbol 193
 
< 0.1%
Modifier Symbol 9
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 2875124
 
12.4%
O 2601571
 
11.2%
D 1826762
 
7.9%
E 1741915
 
7.5%
K 1368253
 
5.9%
N 1119683
 
4.8%
R 1115847
 
4.8%
T 1104328
 
4.8%
Š 981818
 
4.2%
I 914970
 
4.0%
Other values (37) 7486846
32.4%
Lowercase Letter
ValueCountFrequency (%)
a 1331
 
12.0%
o 1126
 
10.1%
n 1061
 
9.5%
e 955
 
8.6%
r 924
 
8.3%
k 546
 
4.9%
m 494
 
4.4%
t 467
 
4.2%
l 462
 
4.2%
s 410
 
3.7%
Other values (30) 3339
30.0%
Decimal Number
ValueCountFrequency (%)
1 1767
23.1%
0 1625
21.3%
5 1272
16.6%
2 972
12.7%
7 543
 
7.1%
3 466
 
6.1%
6 452
 
5.9%
8 265
 
3.5%
4 146
 
1.9%
9 132
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 5599
90.4%
& 239
 
3.9%
, 209
 
3.4%
/ 142
 
2.3%
' 2
 
< 0.1%
* 2
 
< 0.1%
; 1
 
< 0.1%
§ 1
 
< 0.1%
Modifier Symbol
ValueCountFrequency (%)
´ 6
66.7%
¨ 3
33.3%
Space Separator
ValueCountFrequency (%)
140282
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 126043
100.0%
Math Symbol
ValueCountFrequency (%)
+ 193
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23148232
98.8%
Common 280376
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 2875124
 
12.4%
O 2601571
 
11.2%
D 1826762
 
7.9%
E 1741915
 
7.5%
K 1368253
 
5.9%
N 1119683
 
4.8%
R 1115847
 
4.8%
T 1104328
 
4.8%
Š 981818
 
4.2%
I 914970
 
4.0%
Other values (77) 7497961
32.4%
Common
ValueCountFrequency (%)
140282
50.0%
- 126043
45.0%
. 5599
 
2.0%
1 1767
 
0.6%
0 1625
 
0.6%
5 1272
 
0.5%
2 972
 
0.3%
7 543
 
0.2%
3 466
 
0.2%
6 452
 
0.2%
Other values (15) 1355
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22198539
94.7%
None 1230069
 
5.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 2875124
13.0%
O 2601571
 
11.7%
D 1826762
 
8.2%
E 1741915
 
7.8%
K 1368253
 
6.2%
N 1119683
 
5.0%
R 1115847
 
5.0%
T 1104328
 
5.0%
I 914970
 
4.1%
S 834818
 
3.8%
Other values (64) 6695268
30.2%
None
ValueCountFrequency (%)
Š 981818
79.8%
Ë 141379
 
11.5%
Í 35065
 
2.9%
Ý 33938
 
2.8%
Ü 11357
 
0.9%
Č 7117
 
0.6%
Á 7012
 
0.6%
Ö 5740
 
0.5%
Ř 1767
 
0.1%
Ě 1729
 
0.1%
Other values (28) 3147
 
0.3%

DrVoz
Categorical

Distinct44
Distinct (%)< 0.1%
Missing9
Missing (%)< 0.1%
Memory size61.9 MiB
OSOBNÍ AUTOMOBIL
2945168 
NÁKLADNÍ AUTOMOBIL
478739 
MOTOCYKL
 
218591
NÁKLADNÍ PŘÍVĚS
 
178263
NÁKLADNÍ NÁVĚS
 
51215
Other values (39)
 
187024

Length

Max length30
Median length16
Mean length15.659102
Min length5

Characters and Unicode

Total characters63560296
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowOSOBNÍ AUTOMOBIL
2nd rowMOTOCYKL
3rd rowOSOBNÍ AUTOMOBIL
4th rowOSOBNÍ AUTOMOBIL
5th rowOSOBNÍ AUTOMOBIL

Common Values

ValueCountFrequency (%)
OSOBNÍ AUTOMOBIL 2945168
72.6%
NÁKLADNÍ AUTOMOBIL 478739
 
11.8%
MOTOCYKL 218591
 
5.4%
NÁKLADNÍ PŘÍVĚS 178263
 
4.4%
NÁKLADNÍ NÁVĚS 51215
 
1.3%
PŘÍPOJNÉ VOZIDLO 26695
 
0.7%
SPECIÁLNÍ AUTOMOBIL 23324
 
0.6%
TRAKTOR 21319
 
0.5%
AUTOBUS 21273
 
0.5%
TAHAČ NÁVĚSŮ 19947
 
0.5%
Other values (34) 74466
 
1.8%

Length

2023-03-30T21:21:30.155053image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
automobil 3447232
43.8%
osobní 2945168
37.4%
nákladní 716034
 
9.1%
motocykl 218591
 
2.8%
přívěs 201937
 
2.6%
návěs 57845
 
0.7%
vozidlo 42738
 
0.5%
speciální 33801
 
0.4%
traktor 32637
 
0.4%
přípojné 26695
 
0.3%
Other values (39) 151636
 
1.9%

Most occurring characters

ValueCountFrequency (%)
O 13479524
21.2%
B 6413977
10.1%
N 4551492
 
7.2%
L 4486312
 
7.1%
A 4303533
 
6.8%
Í 3954618
 
6.2%
T 3833802
 
6.0%
3815314
 
6.0%
M 3670855
 
5.8%
I 3523780
 
5.5%
Other values (24) 11527089
18.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 59740357
94.0%
Space Separator 3815314
 
6.0%
Other Punctuation 4624
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 13479524
22.6%
B 6413977
10.7%
N 4551492
 
7.6%
L 4486312
 
7.5%
A 4303533
 
7.2%
Í 3954618
 
6.6%
T 3833802
 
6.4%
M 3670855
 
6.1%
I 3523780
 
5.9%
U 3505461
 
5.9%
Other values (21) 8017003
13.4%
Space Separator
ValueCountFrequency (%)
3815314
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4624
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 59740357
94.0%
Common 3819939
 
6.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 13479524
22.6%
B 6413977
10.7%
N 4551492
 
7.6%
L 4486312
 
7.5%
A 4303533
 
7.2%
Í 3954618
 
6.6%
T 3833802
 
6.4%
M 3670855
 
6.1%
I 3523780
 
5.9%
U 3505461
 
5.9%
Other values (21) 8017003
13.4%
Common
ValueCountFrequency (%)
3815314
99.9%
. 4624
 
0.1%
- 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58118704
91.4%
None 5441592
 
8.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 13479524
23.2%
B 6413977
11.0%
N 4551492
 
7.8%
L 4486312
 
7.7%
A 4303533
 
7.4%
T 3833802
 
6.6%
3815314
 
6.6%
M 3670855
 
6.3%
I 3523780
 
6.1%
U 3505461
 
6.0%
Other values (14) 6534654
11.2%
None
ValueCountFrequency (%)
Í 3954618
72.7%
Á 839624
 
15.4%
Ě 281026
 
5.2%
Ř 234357
 
4.3%
Č 37229
 
0.7%
Ý 31672
 
0.6%
É 31170
 
0.6%
Ů 20994
 
0.4%
Š 10853
 
0.2%
Ž 49
 
< 0.1%

ObchOznTyp
Categorical

Distinct70031
Distinct (%)1.7%
Missing920
Missing (%)< 0.1%
Memory size61.9 MiB
OCTAVIA
 
147029
FABIA
 
133111
OCTAVIA (1Z)
 
93173
FELICIA
 
88914
FABIA (6Y)
 
66736
Other values (70026)
3529126 

Length

Max length40
Median length34
Mean length7.9063298
Min length1

Characters and Unicode

Total characters32084590
Distinct characters115
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34541 ?
Unique (%)0.9%

Sample

1st row3
2nd rowETZ 150
3rd row3008
4th row1202
5th rowFOCUS (DA3)

Common Values

ValueCountFrequency (%)
OCTAVIA 147029
 
3.6%
FABIA 133111
 
3.3%
OCTAVIA (1Z) 93173
 
2.3%
FELICIA 88914
 
2.2%
FABIA (6Y) 66736
 
1.6%
FABIA (5J) 61747
 
1.5%
OCTAVIA (1U) 54364
 
1.3%
GOLF 43060
 
1.1%
FOCUS 37611
 
0.9%
OCTAVIA (5E) 34197
 
0.8%
Other values (70021) 3298147
81.3%

Length

2023-03-30T21:21:30.268504image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
octavia 374607
 
5.9%
fabia 322178
 
5.1%
combi 125827
 
2.0%
felicia 111039
 
1.8%
1z 106908
 
1.7%
6y 103315
 
1.6%
golf 91858
 
1.4%
focus 85514
 
1.3%
passat 84176
 
1.3%
5j 83097
 
1.3%
Other values (37400) 4847205
76.5%

Most occurring characters

ValueCountFrequency (%)
A 3610381
 
11.3%
2453120
 
7.6%
I 1877970
 
5.9%
O 1707037
 
5.3%
T 1519030
 
4.7%
C 1480992
 
4.6%
R 1305626
 
4.1%
S 1253040
 
3.9%
E 1242015
 
3.9%
( 1228096
 
3.8%
Other values (105) 14407283
44.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 22520403
70.2%
Decimal Number 4286629
 
13.4%
Space Separator 2453120
 
7.6%
Open Punctuation 1228096
 
3.8%
Close Punctuation 1227888
 
3.8%
Dash Punctuation 150735
 
0.5%
Other Punctuation 117609
 
0.4%
Lowercase Letter 78817
 
0.2%
Modifier Symbol 20115
 
0.1%
Math Symbol 1167
 
< 0.1%
Other values (2) 11
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 3610381
16.0%
I 1877970
 
8.3%
O 1707037
 
7.6%
T 1519030
 
6.7%
C 1480992
 
6.6%
R 1305626
 
5.8%
S 1253040
 
5.6%
E 1242015
 
5.5%
N 933275
 
4.1%
F 896554
 
4.0%
Other values (36) 6694483
29.7%
Lowercase Letter
ValueCountFrequency (%)
i 38472
48.8%
a 5264
 
6.7%
o 4877
 
6.2%
r 4711
 
6.0%
e 2659
 
3.4%
n 2612
 
3.3%
t 2564
 
3.3%
x 2156
 
2.7%
s 1908
 
2.4%
d 1572
 
2.0%
Other values (27) 12022
 
15.3%
Other Punctuation
ValueCountFrequency (%)
. 70912
60.3%
/ 41954
35.7%
, 2237
 
1.9%
* 1723
 
1.5%
! 696
 
0.6%
' 51
 
< 0.1%
& 16
 
< 0.1%
@ 7
 
< 0.1%
; 7
 
< 0.1%
" 3
 
< 0.1%
Other values (3) 3
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 872186
20.3%
1 694798
16.2%
5 512153
11.9%
3 503551
11.7%
2 492042
11.5%
6 411225
9.6%
4 287524
 
6.7%
7 216731
 
5.1%
8 193044
 
4.5%
9 103375
 
2.4%
Modifier Symbol
ValueCountFrequency (%)
´ 20111
> 99.9%
¨ 4
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2453120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1228096
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1227888
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 150735
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1167
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Control
ValueCountFrequency (%)
 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22599220
70.4%
Common 9485370
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 3610381
16.0%
I 1877970
 
8.3%
O 1707037
 
7.6%
T 1519030
 
6.7%
C 1480992
 
6.6%
R 1305626
 
5.8%
S 1253040
 
5.5%
E 1242015
 
5.5%
N 933275
 
4.1%
F 896554
 
4.0%
Other values (73) 6773300
30.0%
Common
ValueCountFrequency (%)
2453120
25.9%
( 1228096
12.9%
) 1227888
12.9%
0 872186
 
9.2%
1 694798
 
7.3%
5 512153
 
5.4%
3 503551
 
5.3%
2 492042
 
5.2%
6 411225
 
4.3%
4 287524
 
3.0%
Other values (22) 802787
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31998786
99.7%
None 85804
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 3610381
 
11.3%
2453120
 
7.7%
I 1877970
 
5.9%
O 1707037
 
5.3%
T 1519030
 
4.7%
C 1480992
 
4.6%
R 1305626
 
4.1%
S 1253040
 
3.9%
E 1242015
 
3.9%
( 1228096
 
3.8%
Other values (71) 14321479
44.8%
None
ValueCountFrequency (%)
Ý 24389
28.4%
Í 23232
27.1%
´ 20111
23.4%
Á 12833
15.0%
É 1759
 
2.1%
í 723
 
0.8%
ý 638
 
0.7%
Č 581
 
0.7%
Ü 323
 
0.4%
á 313
 
0.4%
Other values (24) 902
 
1.1%

Ct
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct134
Distinct (%)< 0.1%
Missing3
Missing (%)< 0.1%
Memory size61.9 MiB
M1
2874865 
N1
304726 
O1
 
146678
LC
 
117237
N3
 
113281
Other values (129)
502219 

Length

Max length7
Median length2
Mean length2.0580985
Min length1

Characters and Unicode

Total characters8353834
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st rowM1
2nd rowL3e
3rd rowM1
4th rowM1
5th rowM1

Common Values

ValueCountFrequency (%)
M1 2874865
70.8%
N1 304726
 
7.5%
O1 146678
 
3.6%
LC 117237
 
2.9%
N3 113281
 
2.8%
O4 79929
 
2.0%
M1G 76192
 
1.9%
L3e 72527
 
1.8%
N2 63815
 
1.6%
O2 44460
 
1.1%
Other values (124) 165296
 
4.1%

Length

2023-03-30T21:21:30.372191image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
m1 2874865
70.8%
n1 304726
 
7.5%
o1 146678
 
3.6%
lc 117237
 
2.9%
n3 113281
 
2.8%
o4 79929
 
2.0%
m1g 76192
 
1.9%
l3e 72527
 
1.8%
n2 63815
 
1.6%
o2 44460
 
1.1%
Other values (120) 165296
 
4.1%

Most occurring characters

ValueCountFrequency (%)
1 3467364
41.5%
M 2973394
35.6%
N 530513
 
6.4%
O 289487
 
3.5%
3 235650
 
2.8%
L 225373
 
2.7%
G 123087
 
1.5%
C 117279
 
1.4%
2 116014
 
1.4%
4 93224
 
1.1%
Other values (26) 182449
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4346332
52.0%
Decimal Number 3916316
46.9%
Lowercase Letter 88468
 
1.1%
Dash Punctuation 2234
 
< 0.1%
Space Separator 374
 
< 0.1%
Other Punctuation 110
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 2973394
68.4%
N 530513
 
12.2%
O 289487
 
6.7%
L 225373
 
5.2%
G 123087
 
2.8%
C 117279
 
2.7%
T 46822
 
1.1%
A 16328
 
0.4%
E 8042
 
0.2%
S 7944
 
0.2%
Other values (9) 8063
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 3467364
88.5%
3 235650
 
6.0%
2 116014
 
3.0%
4 93224
 
2.4%
7 2905
 
0.1%
5 933
 
< 0.1%
6 226
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 84685
95.7%
a 3045
 
3.4%
s 443
 
0.5%
b 279
 
0.3%
p 12
 
< 0.1%
n 4
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 106
96.4%
* 4
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 2234
100.0%
Space Separator
ValueCountFrequency (%)
374
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4434800
53.1%
Common 3919034
46.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 2973394
67.0%
N 530513
 
12.0%
O 289487
 
6.5%
L 225373
 
5.1%
G 123087
 
2.8%
C 117279
 
2.6%
e 84685
 
1.9%
T 46822
 
1.1%
A 16328
 
0.4%
E 8042
 
0.2%
Other values (15) 19790
 
0.4%
Common
ValueCountFrequency (%)
1 3467364
88.5%
3 235650
 
6.0%
2 116014
 
3.0%
4 93224
 
2.4%
7 2905
 
0.1%
- 2234
 
0.1%
5 933
 
< 0.1%
374
 
< 0.1%
6 226
 
< 0.1%
. 106
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8353834
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3467364
41.5%
M 2973394
35.6%
N 530513
 
6.4%
O 289487
 
3.5%
3 235650
 
2.8%
L 225373
 
2.7%
G 123087
 
1.5%
C 117279
 
1.4%
2 116014
 
1.4%
4 93224
 
1.1%
Other values (26) 182449
 
2.2%
Distinct21604
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
Minimum1753-01-01 00:00:00
Maximum2030-12-22 00:00:00
2023-03-30T21:21:30.470571image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:21:30.568505image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Km
Real number (ℝ)

Distinct505976
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158357.07
Minimum0
Maximum9944330
Zeros312244
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size61.9 MiB
2023-03-30T21:21:30.668256image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q160064
median145768
Q3221072
95-th percentile360349.6
Maximum9944330
Range9944330
Interquartile range (IQR)161008

Descriptive statistics

Standard deviation142933.9
Coefficient of variation (CV)0.90260511
Kurtosis121.75919
Mean158357.07
Median Absolute Deviation (MAD)80391
Skewness4.9375645
Sum6.4277279 × 1011
Variance2.0430101 × 1010
MonotonicityNot monotonic
2023-03-30T21:21:30.771514image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 312244
 
7.7%
1 2227
 
0.1%
3 1111
 
< 0.1%
7 911
 
< 0.1%
4 903
 
< 0.1%
8 859
 
< 0.1%
10 849
 
< 0.1%
6 838
 
< 0.1%
9 815
 
< 0.1%
11 775
 
< 0.1%
Other values (505966) 3737477
92.1%
ValueCountFrequency (%)
0 312244
7.7%
1 2227
 
0.1%
2 605
 
< 0.1%
3 1111
 
< 0.1%
4 903
 
< 0.1%
5 719
 
< 0.1%
6 838
 
< 0.1%
7 911
 
< 0.1%
8 859
 
< 0.1%
9 815
 
< 0.1%
ValueCountFrequency (%)
9944330 1
< 0.1%
9633091 1
< 0.1%
9619873 1
< 0.1%
9584128 1
< 0.1%
9455994 1
< 0.1%
9445862 1
< 0.1%
8435123 1
< 0.1%
8222253 1
< 0.1%
8108355 1
< 0.1%
8048336 1
< 0.1%

Zavady
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4059009
Missing (%)100.0%
Memory size61.9 MiB

VyslSTK
Categorical

Distinct3
Distinct (%)< 0.1%
Missing52
Missing (%)< 0.1%
Memory size61.9 MiB
způsobilé
3772740 
částečně způsobilé
 
251795
nezpůsobilé
 
34422

Length

Max length18
Median length9
Mean length9.5752707
Min length9

Characters and Unicode

Total characters38865612
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowzpůsobilé
2nd rowzpůsobilé
3rd rowzpůsobilé
4th rowzpůsobilé
5th rowzpůsobilé

Common Values

ValueCountFrequency (%)
způsobilé 3772740
92.9%
částečně způsobilé 251795
 
6.2%
nezpůsobilé 34422
 
0.8%
(Missing) 52
 
< 0.1%

Length

2023-03-30T21:21:30.865486image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:30.977811image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
způsobilé 4024535
93.4%
částečně 251795
 
5.8%
nezpůsobilé 34422
 
0.8%

Most occurring characters

ValueCountFrequency (%)
s 4310752
11.1%
z 4058957
10.4%
p 4058957
10.4%
ů 4058957
10.4%
o 4058957
10.4%
b 4058957
10.4%
i 4058957
10.4%
l 4058957
10.4%
é 4058957
10.4%
č 503590
 
1.3%
Other values (6) 1579614
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 38613817
99.4%
Space Separator 251795
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 4310752
11.2%
z 4058957
10.5%
p 4058957
10.5%
ů 4058957
10.5%
o 4058957
10.5%
b 4058957
10.5%
i 4058957
10.5%
l 4058957
10.5%
é 4058957
10.5%
č 503590
 
1.3%
Other values (5) 1327819
 
3.4%
Space Separator
ValueCountFrequency (%)
251795
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38613817
99.4%
Common 251795
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 4310752
11.2%
z 4058957
10.5%
p 4058957
10.5%
ů 4058957
10.5%
o 4058957
10.5%
b 4058957
10.5%
i 4058957
10.5%
l 4058957
10.5%
é 4058957
10.5%
č 503590
 
1.3%
Other values (5) 1327819
 
3.4%
Common
ValueCountFrequency (%)
251795
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29740518
76.5%
None 9125094
 
23.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 4310752
14.5%
z 4058957
13.6%
p 4058957
13.6%
o 4058957
13.6%
b 4058957
13.6%
i 4058957
13.6%
l 4058957
13.6%
e 286217
 
1.0%
n 286217
 
1.0%
t 251795
 
0.8%
None
ValueCountFrequency (%)
ů 4058957
44.5%
é 4058957
44.5%
č 503590
 
5.5%
á 251795
 
2.8%
ě 251795
 
2.8%

VyslEmise
Categorical

IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing1440714
Missing (%)35.5%
Memory size61.9 MiB
vyhovuje
2610115 
nevyhovuje
 
7186
částečně vyhovuje
 
994

Length

Max length17
Median length8
Mean length8.0089058
Min length8

Characters and Unicode

Total characters20969678
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowvyhovuje
2nd rowvyhovuje
3rd rowvyhovuje
4th rowvyhovuje
5th rowvyhovuje

Common Values

ValueCountFrequency (%)
vyhovuje 2610115
64.3%
nevyhovuje 7186
 
0.2%
částečně vyhovuje 994
 
< 0.1%
(Missing) 1440714
35.5%

Length

2023-03-30T21:21:31.054272image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:31.130984image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
vyhovuje 2611109
99.7%
nevyhovuje 7186
 
0.3%
částečně 994
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
v 5236590
25.0%
e 2626475
12.5%
y 2618295
12.5%
h 2618295
12.5%
o 2618295
12.5%
u 2618295
12.5%
j 2618295
12.5%
n 8180
 
< 0.1%
č 1988
 
< 0.1%
á 994
 
< 0.1%
Other values (4) 3976
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20968684
> 99.9%
Space Separator 994
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
v 5236590
25.0%
e 2626475
12.5%
y 2618295
12.5%
h 2618295
12.5%
o 2618295
12.5%
u 2618295
12.5%
j 2618295
12.5%
n 8180
 
< 0.1%
č 1988
 
< 0.1%
á 994
 
< 0.1%
Other values (3) 2982
 
< 0.1%
Space Separator
ValueCountFrequency (%)
994
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20968684
> 99.9%
Common 994
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
v 5236590
25.0%
e 2626475
12.5%
y 2618295
12.5%
h 2618295
12.5%
o 2618295
12.5%
u 2618295
12.5%
j 2618295
12.5%
n 8180
 
< 0.1%
č 1988
 
< 0.1%
á 994
 
< 0.1%
Other values (3) 2982
 
< 0.1%
Common
ValueCountFrequency (%)
994
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20965702
> 99.9%
None 3976
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
v 5236590
25.0%
e 2626475
12.5%
y 2618295
12.5%
h 2618295
12.5%
o 2618295
12.5%
u 2618295
12.5%
j 2618295
12.5%
n 8180
 
< 0.1%
s 994
 
< 0.1%
t 994
 
< 0.1%
None
ValueCountFrequency (%)
č 1988
50.0%
á 994
25.0%
ě 994
25.0%

DTKont
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9089226
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.9 MiB
2023-03-30T21:21:31.190801image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4038758
Coefficient of variation (CV)0.48261023
Kurtosis-1.0973545
Mean2.9089226
Median Absolute Deviation (MAD)1
Skewness0.13585636
Sum11807343
Variance1.9708673
MonotonicityNot monotonic
2023-03-30T21:21:31.251211image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 909527
22.4%
1 875989
21.6%
4 810983
20.0%
2 802980
19.8%
5 604920
14.9%
6 53989
 
1.3%
7 621
 
< 0.1%
ValueCountFrequency (%)
1 875989
21.6%
2 802980
19.8%
3 909527
22.4%
4 810983
20.0%
5 604920
14.9%
6 53989
 
1.3%
7 621
 
< 0.1%
ValueCountFrequency (%)
7 621
 
< 0.1%
6 53989
 
1.3%
5 604920
14.9%
4 810983
20.0%
3 909527
22.4%
2 802980
19.8%
1 875989
21.6%

ZavA
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:31.322052image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:31.398363image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

ZavB
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:31.464530image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:31.545750image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

ZavC
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:31.609138image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:31.685862image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

Zav0
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:31.750281image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:31.827249image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

Zav1
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:31.891350image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:31.976595image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

Zav2
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:32.041549image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:32.120193image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

Zav3
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:32.181869image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:32.259423image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

Zav4
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:32.329321image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:32.410863image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

Zav5
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:32.479705image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:32.564120image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

Zav6
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:32.631684image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:32.716147image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

Zav7
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:32.778802image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:32.858642image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

Zav8
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:32.929452image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:33.012511image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

Zav9
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.9 MiB
0
4059009 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4059009
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4059009
100.0%

Length

2023-03-30T21:21:33.074322image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-30T21:21:33.154909image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4059009
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4059009
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4059009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059009
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4059009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059009
100.0%

StariDnu
Real number (ℝ)

Distinct21604
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6686.4988
Minimum-2902
Maximum98625
Zeros0
Zeros (%)0.0%
Negative17
Negative (%)< 0.1%
Memory size61.9 MiB
2023-03-30T21:21:33.238002image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-2902
5-th percentile2641
Q14515
median6153
Q37944
95-th percentile11795
Maximum98625
Range101527
Interquartile range (IQR)3429

Descriptive statistics

Standard deviation5215.9578
Coefficient of variation (CV)0.7800731
Kurtosis202.93044
Mean6686.4988
Median Absolute Deviation (MAD)1707
Skewness11.984219
Sum2.7140559 × 1010
Variance27206216
MonotonicityNot monotonic
2023-03-30T21:21:33.338189image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9506 9595
 
0.2%
8776 9543
 
0.2%
9141 9488
 
0.2%
98625 8564
 
0.2%
8411 7749
 
0.2%
9872 7647
 
0.2%
10237 5730
 
0.1%
10602 4520
 
0.1%
12063 4451
 
0.1%
11333 4403
 
0.1%
Other values (21594) 3987319
98.2%
ValueCountFrequency (%)
-2902 1
< 0.1%
-2901 1
< 0.1%
-2892 1
< 0.1%
-2817 1
< 0.1%
-2752 1
< 0.1%
-2744 1
< 0.1%
-2737 1
< 0.1%
-2726 1
< 0.1%
-2722 1
< 0.1%
-2683 1
< 0.1%
ValueCountFrequency (%)
98625 8564
0.2%
98585 2
 
< 0.1%
98562 1
 
< 0.1%
98560 1
 
< 0.1%
98533 1
 
< 0.1%
98471 1
 
< 0.1%
98450 1
 
< 0.1%
98446 1
 
< 0.1%
98393 1
 
< 0.1%
98365 1
 
< 0.1%

Interactions

2023-03-30T21:20:53.817600image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:38.530635image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:46.820988image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:50.339782image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:54.739019image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:40.932432image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:47.742723image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:51.234630image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:55.240502image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:42.922273image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:48.210195image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:51.704068image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:55.723783image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:44.865905image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:48.711433image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-30T21:20:52.188661image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Correlations

2023-03-30T21:21:33.428061image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
STKKmDTKontStariDnuDrTPDrVozVyslSTKVyslEmise
STK1.0000.0100.0020.0840.2970.1490.1310.041
Km0.0101.000-0.0000.1940.0130.0670.0090.006
DTKont0.002-0.0001.0000.0170.0350.0370.0050.004
StariDnu0.0840.1940.0171.0000.1210.1480.0480.006
DrTP0.2970.0130.0350.1211.0000.1800.1230.015
DrVoz0.1490.0670.0370.1480.1801.0000.0490.012
VyslSTK0.1310.0090.0050.0480.1230.0491.0000.136
VyslEmise0.0410.0060.0040.0060.0150.0120.1361.000

Missing values

2023-03-30T21:20:58.943609image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-03-30T21:21:06.045323image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-03-30T21:21:21.024716image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

STKDrTPVINDatKontTypMotTZnDrVozObchOznTypCtDatPrvRegKmZavadyVyslSTKVyslEmiseDTKontZavAZavBZavCZav0Zav1Zav2Zav3Zav4Zav5Zav6Zav7Zav8Zav9StariDnu
03122Evidenční kontrolaJMZBLA2G6012585042018-01-02 11:03:12.833LFMAZDAOSOBNÍ AUTOMOBIL3M12011-02-1084818NaNzpůsobiléNaN200000000000004353
13205Evidenční kontrola41504172018-01-02 11:06:07.617EM150.2MZMOTOCYKLETZ 150L3e1989-01-0138828NaNzpůsobiléNaN2000000000000012428
23114Evidenční kontrolaVF3MJAHXHGS2801682018-01-02 11:15:08.083AH01PEUGEOTOSOBNÍ AUTOMOBIL3008M12017-01-0939227NaNzpůsobiléNaN200000000000002193
33618Evidenční kontrola46998452018-01-02 11:19:22.9671202ŠKODAOSOBNÍ AUTOMOBIL1202M11979-06-0438951NaNzpůsobiléNaN2000000000000015927
43748Evidenční kontrolaWF0SXXGCDSAU067302018-01-02 11:30:25.420GPDCFORDOSOBNÍ AUTOMOBILFOCUS (DA3)M12010-06-29254194NaNzpůsobiléNaN200000000000004579
53846Evidenční kontrolaJTJBC11A4024434272018-01-02 11:26:50.9672GRLEXUSOSOBNÍ AUTOMOBILRX450HM12012-09-24130258NaNzpůsobiléNaN200000000000003761
63307Před registracíW0922S235HNZ180702018-01-02 13:15:50.550NaNZ-TRAILERPŘÍPOJNÉ VOZIDLOAT35-22/60SW2-XO22017-07-270NaNzpůsobiléNaN200000000000001994
73755Před registracíTMBRD75L8A60126282018-01-02 12:11:56.770CBDBŠKODAOSOBNÍ AUTOMOBILYETIM12009-12-28218933NaNzpůsobilévyhovuje200000000000004762
83124Evidenční kontrolaWV2ZZZ7HZ9H0795902018-01-02 11:57:15.020BNZVWOSOBNÍ AUTOMOBILCARAVELLEM12008-12-08235865NaNzpůsobiléNaN200000000000005147
93710pravidelnáWV2ZZZ7HZFH0623772018-01-02 11:54:17.927CAAVWOSOBNÍ AUTOMOBILTRANSPORTER (7HC)M12015-01-1959557NaNzpůsobilévyhovuje200000000000002914
STKDrTPVINDatKontTypMotTZnDrVozObchOznTypCtDatPrvRegKmZavadyVyslSTKVyslEmiseDTKontZavAZavBZavCZav0Zav1Zav2Zav3Zav4Zav5Zav6Zav7Zav8Zav9StariDnu
40573963402pravidelnáW0L0SBF08W30342032018-12-04 12:25:36.900X10XEOPELOSOBNÍ AUTOMOBILCORSAM11998-07-09185759NaNzpůsobilévyhovuje200000000000008952
40573973733Před registracíTMBBF65JX730238552018-12-05 08:13:49.760BMSŠKODAOSOBNÍ AUTOMOBILFABIAM12007-09-24178481NaNzpůsobilévyhovuje300000000000005588
40573983307pravidelnáWF0EXXGBBECY744332018-12-04 12:43:52.707TXBAFORDOSOBNÍ AUTOMOBILMONDEOM12012-10-3063194NaNzpůsobilévyhovuje200000000000003725
40573993758pravidelnáUU1HSDARN444491572018-12-05 10:22:59.797K4MA6DACIAOSOBNÍ AUTOMOBILDUSTER (SD)M12010-12-2097509NaNzpůsobilévyhovuje300000000000004405
40574003712pravidelnáVF1FLBCA63V1781482018-12-05 08:18:51.993F9QU7RENAULTNÁKLADNÍ AUTOMOBILTRAFICN12006-12-11223386NaNzpůsobilévyhovuje300000000000005875
40574013762pravidelnáNMTBE3JE10R0973412018-12-05 11:27:04.4071ZRTOYOTAOSOBNÍ AUTOMOBILCOROLLAM12014-12-0124283NaNzpůsobilévyhovuje300000000000002963
40574023737pravidelnáVSSZZZ6LZ3R2510582018-12-05 09:10:54.210BBYSEATOSOBNÍ AUTOMOBILCORDOBA (6L)M12003-09-30181310NaNzpůsobilévyhovuje300000000000007043
40574033223Evidenční kontrolaTMBHB46YX132145752018-12-05 12:20:05.940AMEŠKODAOSOBNÍ AUTOMOBILFABIAM12001-04-05267412NaNzpůsobiléNaN300000000000007951
40574053301pravidelná129732018-12-05 13:40:54.900Z4001ZETORTRAKTOR4011T11964-10-290NaNzpůsobilévyhovuje3000000000000021258
40574063210Evidenční kontrolaTMBAG7NEXH00095862018-12-05 13:14:35.997CXXŠKODAOSOBNÍ AUTOMOBILOCTAVIA (5E)M12016-06-15129758NaNzpůsobiléNaN300000000000002401